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Variational and Information Flows in Machine Learning and Optimal Transport
By Wuchen Li
0 - Default Title
Description
Variational and stochastic flows on measure spaces are ubiquitous in machine learning and generative modeling. Optimal transport and diffeomorphic flows provide powerful frameworks to analyze such trajectories of distributions with elegant notions from differential geometry, such as geodesics, gradient and Hamiltonian flows. Recently, mean field control and mean field games offered a general optimal control variational view on learning problems. The four independent chapters in this book address the question of how the presented tools lead us to better understanding and further development of machine learning and generative models.
Product details
Binding:
Paperback
Number of Pages:
268
Release Date:
2025-07-19
Publication Date:
2025-07-19
Publisher:
Springer Nature Switzerland
Languages:
Original:
English
ISBN10:
3031927303
ISBN13:
9783031927300
GPSR Manufacturer Reference:
Weight:
455 g
Height:
168 cm
Width:
240 cm
Thickness:
15 cm
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